A New Approximation with Radial Basis Function Type Neural Networks for Fault Diagnosis in Induction Motor Drive System

摘要

It is developed a radial basis function neural network based fault diagnosis system to perform mechanical faults of induction motor drive system. The usage of changeable load conditions affects the performance and faults of AC drives-especially induction motor control systems directly. In this paper, a new approximation under a radial basis function neural network for screwing mechanical fault with different type neural networks -classic and fast back-propagation algorithms for the application of AC drive motor control systems to increase the performance as a basic and important study is synchronously considered at the same time.